Predictive monitoring systems are implemented in a variety of applications such as vehicles and computers. Such systems may be used to predict any components in need of maintenance or subject to impending failure.
In many mechanical systems, monitoring vibration is the favored method of predictive monitoring. Although vibration is an inherent part of most mechanical systems, excessive vibration levels can indicate a problem. High vibration levels may indicate problems such as loose components, failing components, misaligned couplings, resonance and deformation, or mechanical or electromagnetic imbalance. Typically, vibration is monitored through the use of accelerometers permanently or magnetically mounted to system components. The level of vibration is typically measured as a function of frequency and amplitude. A vibration plot may also be visualized in three dimensions as a function of frequency, amplitude, and position. Further, the data may be analyzed via moving range analysis, wherein values are assessed over time. But, vibration data alone cannot accurately predict an impending failure, which is highly dependent on the normal operating conditions of a given system component.
If a component in a system fails, it can irreparably damage the component or even the system at large. Thus, if maintenance is performed, or the component is automatically disabled, further damage can be avoided. On the other hand, overly sensitive alert systems can lead to nuisance alerts. In a critical system component, unnecessary shutoff can be dangerous. Further, in a complex system, it may be impractical for an operator to disassemble a complex system to shut down a nonessential component.
Thus, what is needed is a predictive monitoring system that can accurately determine when intervention is required, select the appropriate intervention given the circumstances, and automatically act accordingly.